Data for 'Efficient characterisation of large deviations using population dynamics'


Brewer, T., Jack, R., 2018. Data for 'Efficient characterisation of large deviations using population dynamics'. University of Bath. https://doi.org/10.15125/BATH-00457.


Dataset abstract

We have produced a research paper 'Efficient characterisation of large deviations using population dynamics' investigating the nature of rare events in the SSEP. We study activity distribiutions of this process on a one dimensional lattice with periodic boundary conditions. The process is simulated using a C++ code and parallelisation is used to increase computational efficiency. The two parallelisation methods that we use are OpenMP and MPI and these are stored in a repository in this data set. The codes are designed such that they can be used to study rare events in other processes and study observables other than activity. The dataset includes .txt and .mat files output by the C++ files and by the .m files used for processing. Further .m MATLAB files are used to produce the data and tables within the paper.

Title: Data for 'Efficient characterisation of large deviations using population dynamics'
Keywords: Large Deviations, Efficient Computation, Parallelisation, Numerical Algorithm, Population Dynamics
Subjects: Mathematical sciences > Mathematical Physics
Mathematical sciences > Statistics and Applied Probability
Departments: Faculty of Science > Computer Science
Faculty of Science > Physics
DOI: https://doi.org/10.15125/BATH-00457
URI: https://researchdata.bath.ac.uk/id/eprint/457
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